Summary
Melissa Taane
7/12/2019
knitr::opts_chunk$set(echo = FALSE,cache = TRUE)
library(xlsx)
library(ggplot2)## Registered S3 methods overwritten by 'ggplot2':
## method from
## [.quosures rlang
## c.quosures rlang
## print.quosures rlanglibrary(gplots)##
## Attaching package: 'gplots'## The following object is masked from 'package:stats':
##
## lowesslibrary(gridExtra)
library(corrplot)## corrplot 0.84 loadedlibrary(dplyr)##
## Attaching package: 'dplyr'## The following object is masked from 'package:gridExtra':
##
## combine## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(png)
library(grid)
library(heatmaply)## Loading required package: plotly##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layout## Loading required package: viridis## Loading required package: viridisLite## Registered S3 method overwritten by 'seriation':
## method from
## reorder.hclust gclus##
## ======================
## Welcome to heatmaply version 0.16.0
##
## Type citation('heatmaply') for how to cite the package.
## Type ?heatmaply for the main documentation.
##
## The github page is: https://github.com/talgalili/heatmaply/
## Please submit your suggestions and bug-reports at: https://github.com/talgalili/heatmaply/issues
## Or contact: <tal.galili@gmail.com>
## ======================## Warning: NAs introduced by coercion## Tree.ID Allocation Column Row Rep. measure Height Flower Flower.Level
## 840 IN4E4 F1 2 20 N 7 M N 0
## 1363 IN4FM F1 3 17 N 11 H N 0
## Chl Flav Anth Height08 Height09 HD
## 840 18.511 1.401 0.370 138 234 96
## 1363 59.122 1.640 0.483 166 245 79## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`Tree Plots
Anthocyanin
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.## Warning: Removed 21 rows containing non-finite values (stat_bin).## Warning: Removed 21 rows containing non-finite values (stat_density).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Tree.ID 158 0.26483 0.0016762 0.9733 0.5779
## Residuals 1631 2.80887 0.0017222
- R.squared
## [1] 0.08616099Chlorophyll
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.## Warning: Removed 21 rows containing non-finite values (stat_bin).## Warning: Removed 21 rows containing non-finite values (stat_density).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Tree.ID 158 23815 150.73 0.6775 0.999
## Residuals 1631 362856 222.47
- R.squared
## [1] 0.06158903Flavonol
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.## Warning: Removed 21 rows containing non-finite values (stat_bin).## Warning: Removed 21 rows containing non-finite values (stat_density).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Tree.ID 158 14.876 0.094149 1.8118 1.856e-08 ***
## Residuals 1631 84.754 0.051965
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.149308Height 2018
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 8 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.## Warning: Removed 8 rows containing non-finite values (stat_bin).## Warning: Removed 8 rows containing non-finite values (stat_density).
- ANOVA
## Warning in anova.lm(mod181): ANOVA F-tests on an essentially perfect fit
## are unreliable## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Tree.ID 171 418774 2449 3.9594e+27 < 2.2e-16 ***
## Residuals 1550 0 0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Warning: not plotting observations with leverage one:
## 306, 1600, 1609, 1610, 1611, 1614, 1617, 1622, 1630, 1642, 1644, 1653, 1661, 1680, 1681, 1687, 1690, 1698, 1722
## Warning: not plotting observations with leverage one:
## 306, 1600, 1609, 1610, 1611, 1614, 1617, 1622, 1630, 1642, 1644, 1653, 1661, 1680, 1681, 1687, 1690, 1698, 1722
## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced
- R.squared
## [1] 1Height 2019
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 9 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.## Warning: Removed 9 rows containing non-finite values (stat_bin).## Warning: Removed 9 rows containing non-finite values (stat_density).
- ANOVA
## Warning in anova.lm(mod191): ANOVA F-tests on an essentially perfect fit
## are unreliable## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Tree.ID 170 429289 2525.2 3.72e+27 < 2.2e-16 ***
## Residuals 1550 0 0.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Warning: not plotting observations with leverage one:
## 1599, 1610, 1613, 1616, 1620, 1621, 1629, 1641, 1643, 1652, 1660, 1679, 1680, 1686, 1689, 1697, 1721
## Warning: not plotting observations with leverage one:
## 1599, 1610, 1613, 1616, 1620, 1621, 1629, 1641, 1643, 1652, 1660, 1679, 1680, 1686, 1689, 1697, 1721
## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced
- R.squared
## [1] 1Height Difference 2018-2019
## Warning: Removed 1811 rows containing non-finite values (stat_boxplot).
## Warning: Removed 180 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.## Warning: Removed 180 rows containing non-finite values (stat_bin).## Warning: Removed 180 rows containing non-finite values (stat_density).
- Anova
## Warning in anova.lm(modHD1): ANOVA F-tests on an essentially perfect fit
## are unreliable## Analysis of Variance Table
##
## Response: F1$HD5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Tree.ID 170 382183 2248.1 6.9697e+27 < 2.2e-16 ***
## Residuals 1550 0 0.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Warning: not plotting observations with leverage one:
## 1599, 1610, 1613, 1616, 1620, 1621, 1629, 1641, 1643, 1652, 1660, 1679, 1680, 1686, 1689, 1697, 1721
## Warning: not plotting observations with leverage one:
## 1599, 1610, 1613, 1616, 1620, 1621, 1629, 1641, 1643, 1652, 1660, 1679, 1680, 1686, 1689, 1697, 1721
## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced
- R.squared
## [1] 1Leaf Height Plots
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`Anthocyanin
## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).
- ANOVA Anthocyanin and Collection Height
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Height 2 0.0000 1.650e-06 0.001 0.999
## Residuals 1787 3.0326 1.697e-03
##
## Call:
## lm(formula = F1$Anth5 ~ F1$Height)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.108092 -0.027610 -0.000777 0.025741 0.198752
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.737e-05 1.846e-03 -0.036 0.971
## F1$HeightL 8.195e-05 2.452e-03 0.033 0.973
## F1$HeightM 1.049e-04 2.461e-03 0.043 0.966
##
## Residual standard error: 0.04119 on 1787 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 1.089e-06, Adjusted R-squared: -0.001118
## F-statistic: 0.000973 on 2 and 1787 DF, p-value: 0.999- R.squared Collection Height
## [1] 1.08897e-06- ANOVA Anthocyanin High vs Mid Heights
## Analysis of Variance Table
##
## Response: HH$Anth
## Df Sum Sq Mean Sq F value Pr(>F)
## HM$Anth 1 0.000222 0.00022183 0.299 0.5853
## Residuals 157 0.116476 0.00074189
##
## Call:
## lm(formula = HH$Anth ~ HM$Anth)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.074972 -0.017800 -0.001569 0.019434 0.088874
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0003553 0.0021601 0.164 0.870
## HM$Anth -0.0594670 0.1087508 -0.547 0.585
##
## Residual standard error: 0.02724 on 157 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 0.001901, Adjusted R-squared: -0.004456
## F-statistic: 0.299 on 1 and 157 DF, p-value: 0.5853- R.squared Anthocyanin High vs Mid Heights
## [1] 0.001900911- ANOVA Anthocyanin Low vs Mid Heights
## Analysis of Variance Table
##
## Response: HL$Anth
## Df Sum Sq Mean Sq F value Pr(>F)
## HM$Anth 1 0.000092 0.00009166 0.1926 0.6613
## Residuals 157 0.074704 0.00047582
- R.squared Anthocyanin Low vs Mid Heights
## [1] 0.001225476- ANOVA Anthocyanin High vs Low Heights
## Analysis of Variance Table
##
## Response: HH$Anth
## Df Sum Sq Mean Sq F value Pr(>F)
## HL$Anth 1 0.000074 0.00007430 0.1 0.7522
## Residuals 157 0.116624 0.00074283
- R.squared Anthocyanin High vs Low Heights
## [1] 0.000636706Chlorophyll
## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).
- ANOVA Chlorophyll and Collection Height
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Height 2 802 401.03 1.8488 0.1577
## Residuals 1787 387632 216.92
- R.squared Collection Height
## [1] 0.002064874- ANOVA Chlorophyll High vs Mid Heights
## Analysis of Variance Table
##
## Response: HH$Chl
## Df Sum Sq Mean Sq F value Pr(>F)
## HM$Chl 1 439.6 439.57 5.1202 0.02502 *
## Residuals 157 13478.4 85.85
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Chlorophyll High vs Mid Heights
## [1] 0.03158298- ANOVA Chlorophyll Low vs Mid Heights
## Analysis of Variance Table
##
## Response: HL$Chl
## Df Sum Sq Mean Sq F value Pr(>F)
## HM$Chl 1 141.6 141.639 2.4422 0.1201
## Residuals 157 9105.6 57.998
- R.squared Chlorophyll Low vs Mid Heights
## [1] 0.01531687- ANOVA Chlorophyll High vs Low Heights
## Analysis of Variance Table
##
## Response: HH$Chl
## Df Sum Sq Mean Sq F value Pr(>F)
## HL$Chl 1 526.1 526.06 6.1673 0.01406 *
## Residuals 157 13391.9 85.30
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Chlorophyll High vs Low Heights
## [1] 0.03779738Flavonol
## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).
- ANOVA Flavonol and Collection Height
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Height 2 0.001 0.000562 0.0102 0.9899
## Residuals 1787 98.658 0.055209
- R.squared Collection Height
## [1] 1.139096e-05- ANOVA Flavonol High vs Mid Heights
## Analysis of Variance Table
##
## Response: HH$Flav
## Df Sum Sq Mean Sq F value Pr(>F)
## HM$Flav 1 0.0540 0.053997 3.1493 0.0779 .
## Residuals 157 2.6919 0.017146
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flavonol High vs Mid Heights
## [1] 0.01966458- ANOVA Flavonol Low vs Mid Heights
## Analysis of Variance Table
##
## Response: HL$Flav
## Df Sum Sq Mean Sq F value Pr(>F)
## HM$Flav 1 0.1518 0.151825 5.739 0.01777 *
## Residuals 157 4.1534 0.026455
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flavonol Low vs Mid Heights
## [1] 0.0352653- ANOVA Flavonol High vs Low Heights
## Analysis of Variance Table
##
## Response: HH$Flav
## Df Sum Sq Mean Sq F value Pr(>F)
## HL$Flav 1 0.00651 0.0065076 0.373 0.5423
## Residuals 157 2.73937 0.0174482
- R.squared Flavonol High vs Low Heights
## [1] 0.002369954Row Plots
Anthocyanin
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 0.00009 0.00000191 0.0011 1
## Residuals 1740 3.03249 0.00174281
##
## Call:
## lm(formula = F1$Anth5 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.10823 -0.02772 -0.00075 0.02580 0.19883
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.236e-04 6.026e-03 -0.021 0.984
## F1$Row10 -4.004e-04 9.527e-03 -0.042 0.966
## F1$Row11 1.971e-06 8.478e-03 0.000 1.000
## F1$Row12 2.002e-04 9.527e-03 0.021 0.983
## F1$Row13 6.312e-05 9.819e-03 0.006 0.995
## F1$Row14 1.970e-04 9.440e-03 0.021 0.983
## F1$Row15 1.970e-04 9.440e-03 0.021 0.983
## F1$Row16 1.123e-05 9.716e-03 0.001 0.999
## F1$Row17 5.573e-04 1.092e-02 0.051 0.959
## F1$Row18 1.123e-05 9.716e-03 0.001 0.999
## F1$Row19 1.970e-04 9.440e-03 0.021 0.983
## F1$Row2 1.970e-04 9.440e-03 0.021 0.983
## F1$Row20 6.273e-05 8.766e-03 0.007 0.994
## F1$Row21 1.432e-04 9.133e-03 0.016 0.987
## F1$Row22 1.970e-04 9.440e-03 0.021 0.983
## F1$Row23 6.273e-05 8.766e-03 0.007 0.994
## F1$Row24 6.013e-04 9.440e-03 0.064 0.949
## F1$Row25 1.970e-04 9.440e-03 0.021 0.983
## F1$Row26 6.852e-04 9.619e-03 0.071 0.943
## F1$Row27 4.335e-04 9.527e-03 0.045 0.964
## F1$Row28 1.970e-04 9.440e-03 0.021 0.983
## F1$Row29 -4.004e-04 9.527e-03 -0.042 0.966
## F1$Row3 1.970e-04 9.440e-03 0.021 0.983
## F1$Row30 -1.846e-04 9.716e-03 -0.019 0.985
## F1$Row31 -4.212e-04 8.766e-03 -0.048 0.962
## F1$Row32 1.970e-04 8.713e-03 0.023 0.982
## F1$Row33 1.970e-04 9.440e-03 0.021 0.983
## F1$Row34 1.970e-04 8.713e-03 0.023 0.982
## F1$Row35 2.890e-05 8.662e-03 0.003 0.997
## F1$Row36 2.002e-04 9.527e-03 0.021 0.983
## F1$Row37 2.002e-04 9.527e-03 0.021 0.983
## F1$Row38 -1.756e-04 9.619e-03 -0.018 0.985
## F1$Row39 1.970e-04 9.440e-03 0.021 0.983
## F1$Row4 -2.072e-04 9.440e-03 -0.022 0.982
## F1$Row40 1.970e-04 9.440e-03 0.021 0.983
## F1$Row41 3.156e-04 8.567e-03 0.037 0.971
## F1$Row42 3.751e-04 9.440e-03 0.040 0.968
## F1$Row43 2.548e-04 9.619e-03 0.026 0.979
## F1$Row44 4.335e-04 9.527e-03 0.045 0.964
## F1$Row45 6.273e-05 8.766e-03 0.007 0.994
## F1$Row46 5.096e-04 8.766e-03 0.058 0.954
## F1$Row47 -1.109e-04 8.766e-03 -0.013 0.990
## F1$Row48 1.899e-05 9.440e-03 0.002 0.998
## F1$Row49 1.970e-04 8.713e-03 0.023 0.982
## F1$Row5 2.002e-04 9.527e-03 0.021 0.983
## F1$Row50 -1.715e-04 8.178e-03 -0.021 0.983
## F1$Row6 1.970e-04 9.440e-03 0.021 0.983
## F1$Row7 1.970e-04 9.440e-03 0.021 0.983
## F1$Row8 1.970e-04 9.440e-03 0.021 0.983
## F1$Row9 -2.550e-05 9.358e-03 -0.003 0.998
##
## Residual standard error: 0.04175 on 1740 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 3.078e-05, Adjusted R-squared: -0.02813
## F-statistic: 0.001093 on 49 and 1740 DF, p-value: 1- R.squared
## [1] 3.078204e-05Chlorophyll
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 0 0.00 0 1
## Residuals 1740 388434 223.24
##
## Call:
## lm(formula = F1$Chl5 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -40.413 -10.889 1.258 11.488 30.448
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.122e-14 2.157e+00 0 1
## F1$Row10 -5.443e-14 3.410e+00 0 1
## F1$Row11 -5.868e-14 3.034e+00 0 1
## F1$Row12 -4.608e-14 3.410e+00 0 1
## F1$Row13 -4.346e-14 3.514e+00 0 1
## F1$Row14 -4.472e-14 3.379e+00 0 1
## F1$Row15 -5.143e-14 3.379e+00 0 1
## F1$Row16 -4.709e-14 3.477e+00 0 1
## F1$Row17 -2.396e-14 3.909e+00 0 1
## F1$Row18 -4.307e-14 3.477e+00 0 1
## F1$Row19 -8.068e-14 3.379e+00 0 1
## F1$Row2 -3.876e-14 3.379e+00 0 1
## F1$Row20 -5.483e-14 3.137e+00 0 1
## F1$Row21 -5.324e-14 3.269e+00 0 1
## F1$Row22 -5.665e-14 3.379e+00 0 1
## F1$Row23 -5.097e-14 3.137e+00 0 1
## F1$Row24 -3.762e-14 3.379e+00 0 1
## F1$Row25 -4.563e-14 3.379e+00 0 1
## F1$Row26 -5.032e-14 3.443e+00 0 1
## F1$Row27 -5.458e-14 3.410e+00 0 1
## F1$Row28 -4.724e-14 3.379e+00 0 1
## F1$Row29 -3.408e-14 3.410e+00 0 1
## F1$Row3 -4.192e-14 3.379e+00 0 1
## F1$Row30 -5.594e-14 3.477e+00 0 1
## F1$Row31 1.341e-14 3.137e+00 0 1
## F1$Row32 -5.711e-14 3.118e+00 0 1
## F1$Row33 -5.905e-14 3.379e+00 0 1
## F1$Row34 -5.094e-14 3.118e+00 0 1
## F1$Row35 -6.647e-14 3.100e+00 0 1
## F1$Row36 -5.311e-14 3.410e+00 0 1
## F1$Row37 -9.871e-15 3.410e+00 0 1
## F1$Row38 -4.983e-14 3.443e+00 0 1
## F1$Row39 -5.183e-14 3.379e+00 0 1
## F1$Row4 -5.165e-14 3.379e+00 0 1
## F1$Row40 -6.223e-14 3.379e+00 0 1
## F1$Row41 -5.581e-14 3.066e+00 0 1
## F1$Row42 -5.669e-14 3.379e+00 0 1
## F1$Row43 -5.319e-14 3.443e+00 0 1
## F1$Row44 -7.369e-14 3.410e+00 0 1
## F1$Row45 -6.561e-14 3.137e+00 0 1
## F1$Row46 -8.051e-14 3.137e+00 0 1
## F1$Row47 -6.965e-14 3.137e+00 0 1
## F1$Row48 -6.373e-14 3.379e+00 0 1
## F1$Row49 -4.888e-14 3.118e+00 0 1
## F1$Row5 -6.082e-14 3.410e+00 0 1
## F1$Row50 -6.229e-14 2.927e+00 0 1
## F1$Row6 -4.716e-14 3.379e+00 0 1
## F1$Row7 -6.638e-14 3.379e+00 0 1
## F1$Row8 -6.942e-14 3.379e+00 0 1
## F1$Row9 -7.645e-14 3.349e+00 0 1
##
## Residual standard error: 14.94 on 1740 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 1.668e-29, Adjusted R-squared: -0.02816
## F-statistic: 5.924e-28 on 49 and 1740 DF, p-value: 1- R.squared
## [1] 1.668271e-29Flavonol
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 0.200 0.004090 0.0723 1
## Residuals 1740 98.459 0.056585
##
## Call:
## lm(formula = F1$Flav5 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.87631 -0.14319 0.01576 0.15006 0.83162
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0160350 0.0343346 -0.467 0.641
## F1$Row10 0.0122635 0.0542877 0.226 0.821
## F1$Row11 -0.0007709 0.0483081 -0.016 0.987
## F1$Row12 0.0109164 0.0542877 0.201 0.841
## F1$Row13 0.0113525 0.0559472 0.203 0.839
## F1$Row14 0.0109282 0.0537920 0.203 0.839
## F1$Row15 0.0109282 0.0537920 0.203 0.839
## F1$Row16 0.0159958 0.0553629 0.289 0.773
## F1$Row17 0.0285742 0.0622367 0.459 0.646
## F1$Row18 0.0110881 0.0553629 0.200 0.841
## F1$Row19 0.0109282 0.0537920 0.203 0.839
## F1$Row2 0.0109282 0.0537920 0.203 0.839
## F1$Row20 0.0175783 0.0499480 0.352 0.725
## F1$Row21 0.0067765 0.0520404 0.130 0.896
## F1$Row22 0.0109282 0.0537920 0.203 0.839
## F1$Row23 0.0370839 0.0499480 0.742 0.458
## F1$Row24 0.0073530 0.0537920 0.137 0.891
## F1$Row25 0.0109282 0.0537920 0.203 0.839
## F1$Row26 0.0089356 0.0548106 0.163 0.871
## F1$Row27 0.0094440 0.0542877 0.174 0.862
## F1$Row28 0.0109282 0.0537920 0.203 0.839
## F1$Row29 0.0147885 0.0542877 0.272 0.785
## F1$Row3 0.0109282 0.0537920 0.203 0.839
## F1$Row30 0.0118640 0.0553629 0.214 0.830
## F1$Row31 0.0048055 0.0499480 0.096 0.923
## F1$Row32 0.0352480 0.0496477 0.710 0.478
## F1$Row33 0.0109282 0.0537920 0.203 0.839
## F1$Row34 0.0352480 0.0496477 0.710 0.478
## F1$Row35 0.0346724 0.0493591 0.702 0.482
## F1$Row36 0.0124501 0.0542877 0.229 0.819
## F1$Row37 0.0124501 0.0542877 0.229 0.819
## F1$Row38 0.0128693 0.0548106 0.235 0.814
## F1$Row39 0.0109282 0.0537920 0.203 0.839
## F1$Row4 0.0125355 0.0537920 0.233 0.816
## F1$Row40 0.0109282 0.0537920 0.203 0.839
## F1$Row41 0.0218259 0.0488140 0.447 0.655
## F1$Row42 0.0107487 0.0537920 0.200 0.842
## F1$Row43 0.0095752 0.0548106 0.175 0.861
## F1$Row44 0.0109777 0.0542877 0.202 0.840
## F1$Row45 0.0359426 0.0499480 0.720 0.472
## F1$Row46 0.0357126 0.0499480 0.715 0.475
## F1$Row47 0.0350335 0.0499480 0.701 0.483
## F1$Row48 0.0106271 0.0537920 0.198 0.843
## F1$Row49 0.0352480 0.0496477 0.710 0.478
## F1$Row5 0.0124501 0.0542877 0.229 0.819
## F1$Row50 0.0200420 0.0466003 0.430 0.667
## F1$Row6 0.0109282 0.0537920 0.203 0.839
## F1$Row7 0.0109282 0.0537920 0.203 0.839
## F1$Row8 0.0109282 0.0537920 0.203 0.839
## F1$Row9 0.0123251 0.0533211 0.231 0.817
##
## Residual standard error: 0.2379 on 1740 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 0.002032, Adjusted R-squared: -0.02607
## F-statistic: 0.07229 on 49 and 1740 DF, p-value: 1- R.squared
## [1] 0.002031552Height 2018
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 24288 495.68 2.1009 1.659e-05 ***
## Residuals 1672 394486 235.94
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Call:
## lm(formula = F1$H185 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -52.933 -11.518 -0.736 11.531 39.018
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.5699 2.5252 3.394 0.000706 ***
## F1$Row10 -7.3312 3.7081 -1.977 0.048195 *
## F1$Row11 -4.5365 3.3454 -1.356 0.175273
## F1$Row12 -6.7638 3.7081 -1.824 0.068317 .
## F1$Row13 -6.0953 3.8095 -1.600 0.109780
## F1$Row14 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row15 -0.6156 4.1353 -0.149 0.881685
## F1$Row16 -7.9814 3.7738 -2.115 0.034581 *
## F1$Row17 -10.2487 4.1353 -2.478 0.013299 *
## F1$Row18 -5.8621 3.7738 -1.553 0.120521
## F1$Row19 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row2 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row20 -6.0017 3.4444 -1.742 0.081610 .
## F1$Row21 -7.0921 3.5476 -1.999 0.045758 *
## F1$Row22 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row23 -14.8322 3.4444 -4.306 1.76e-05 ***
## F1$Row24 -7.9433 3.6491 -2.177 0.029636 *
## F1$Row25 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row26 -8.4962 3.7081 -2.291 0.022071 *
## F1$Row27 -11.9432 4.1353 -2.888 0.003926 **
## F1$Row28 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row29 -10.9642 4.1966 -2.613 0.009066 **
## F1$Row3 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row30 -8.7014 3.7400 -2.327 0.020106 *
## F1$Row31 -6.0018 3.4262 -1.752 0.080001 .
## F1$Row32 -14.4746 3.4262 -4.225 2.52e-05 ***
## F1$Row33 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row34 -14.4746 3.4262 -4.225 2.52e-05 ***
## F1$Row35 -14.1328 3.4088 -4.146 3.55e-05 ***
## F1$Row36 -8.3034 3.6778 -2.258 0.024093 *
## F1$Row37 -8.3034 3.6778 -2.258 0.024093 *
## F1$Row38 -7.9288 3.7081 -2.138 0.032640 *
## F1$Row39 -2.1704 4.0786 -0.532 0.594691
## F1$Row4 -0.6156 4.1353 -0.149 0.881685
## F1$Row40 -2.1704 4.0786 -0.532 0.594691
## F1$Row41 -11.1135 3.3759 -3.292 0.001015 **
## F1$Row42 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row43 -7.2665 3.7081 -1.960 0.050201 .
## F1$Row44 -8.3034 3.6778 -2.258 0.024093 *
## F1$Row45 -14.3393 3.4444 -4.163 3.30e-05 ***
## F1$Row46 -14.8322 3.4444 -4.306 1.76e-05 ***
## F1$Row47 -13.9652 3.4444 -4.055 5.25e-05 ***
## F1$Row48 -8.5666 3.6491 -2.348 0.019011 *
## F1$Row49 -14.4746 3.4262 -4.225 2.52e-05 ***
## F1$Row5 -0.6879 4.1966 -0.164 0.869820
## F1$Row50 -10.3134 3.2428 -3.180 0.001498 **
## F1$Row6 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row7 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row8 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row9 -7.5595 3.6491 -2.072 0.038456 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15.36 on 1672 degrees of freedom
## (89 observations deleted due to missingness)
## Multiple R-squared: 0.058, Adjusted R-squared: 0.03039
## F-statistic: 2.101 on 49 and 1672 DF, p-value: 1.659e-05- R.squared
## [1] 0.05799867Height 2019
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 36836 751.76 3.2009 1.777e-12 ***
## Residuals 1671 392453 234.86
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Call:
## lm(formula = F1$H195 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -47.068 -9.354 1.204 10.862 38.322
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 12.495 2.519 4.959 7.79e-07 ***
## F1$Row10 -11.677 3.700 -3.156 0.001626 **
## F1$Row11 -7.027 3.338 -2.105 0.035411 *
## F1$Row12 -10.852 3.700 -2.933 0.003399 **
## F1$Row13 -9.877 3.801 -2.599 0.009444 **
## F1$Row14 -11.478 3.669 -3.128 0.001791 **
## F1$Row15 -1.467 4.126 -0.356 0.722127
## F1$Row16 -12.841 3.765 -3.410 0.000664 ***
## F1$Row17 -17.664 4.187 -4.219 2.59e-05 ***
## F1$Row18 -9.476 3.765 -2.517 0.011939 *
## F1$Row19 -11.478 3.669 -3.128 0.001791 **
## F1$Row2 -11.478 3.669 -3.128 0.001791 **
## F1$Row20 -9.992 3.436 -2.908 0.003691 **
## F1$Row21 -10.820 3.540 -3.057 0.002272 **
## F1$Row22 -12.346 3.641 -3.391 0.000713 ***
## F1$Row23 -19.346 3.436 -5.629 2.12e-08 ***
## F1$Row24 -12.133 3.641 -3.333 0.000879 ***
## F1$Row25 -12.346 3.641 -3.391 0.000713 ***
## F1$Row26 -13.026 3.700 -3.521 0.000442 ***
## F1$Row27 -18.724 4.126 -4.538 6.08e-06 ***
## F1$Row28 -12.346 3.641 -3.391 0.000713 ***
## F1$Row29 -15.926 4.187 -3.804 0.000148 ***
## F1$Row3 -11.478 3.669 -3.128 0.001791 **
## F1$Row30 -13.282 3.731 -3.559 0.000382 ***
## F1$Row31 -9.051 3.418 -2.648 0.008180 **
## F1$Row32 -18.857 3.418 -5.516 4.00e-08 ***
## F1$Row33 -12.346 3.641 -3.391 0.000713 ***
## F1$Row34 -18.857 3.418 -5.516 4.00e-08 ***
## F1$Row35 -18.390 3.401 -5.407 7.32e-08 ***
## F1$Row36 -12.785 3.669 -3.484 0.000506 ***
## F1$Row37 -12.785 3.669 -3.484 0.000506 ***
## F1$Row38 -12.200 3.700 -3.298 0.000995 ***
## F1$Row39 -3.186 4.069 -0.783 0.433764
## F1$Row4 -1.467 4.126 -0.356 0.722127
## F1$Row40 -3.186 4.069 -0.783 0.433764
## F1$Row41 -14.762 3.368 -4.383 1.24e-05 ***
## F1$Row42 -12.346 3.641 -3.391 0.000713 ***
## F1$Row43 -11.149 3.700 -3.014 0.002621 **
## F1$Row44 -12.785 3.669 -3.484 0.000506 ***
## F1$Row45 -18.563 3.436 -5.402 7.55e-08 ***
## F1$Row46 -19.346 3.436 -5.629 2.12e-08 ***
## F1$Row47 -18.342 3.436 -5.337 1.07e-07 ***
## F1$Row48 -13.123 3.641 -3.604 0.000322 ***
## F1$Row49 -18.857 3.418 -5.516 4.00e-08 ***
## F1$Row5 -1.640 4.187 -0.392 0.695367
## F1$Row50 -13.308 3.235 -4.113 4.09e-05 ***
## F1$Row6 -11.478 3.669 -3.128 0.001791 **
## F1$Row7 -11.478 3.669 -3.128 0.001791 **
## F1$Row8 -11.478 3.669 -3.128 0.001791 **
## F1$Row9 -12.067 3.641 -3.314 0.000938 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15.33 on 1671 degrees of freedom
## (90 observations deleted due to missingness)
## Multiple R-squared: 0.08581, Adjusted R-squared: 0.059
## F-statistic: 3.201 on 49 and 1671 DF, p-value: 1.777e-12- R.squared
## [1] 0.08580726Height Difference 2018-2019
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 50 rows containing missing values (geom_point).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$HD5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 2380 48.577 0.2137 1
## Residuals 1671 379803 227.291
+R.squared
## [1] 0.00593089Column Plots
Anthocyanin
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).## Warning: Removed 21 rows containing non-finite values (stat_summary).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 0.00038 0.00012737 0.074 0.9739
## Residuals 1786 3.07332 0.00172078
- R.squared
## [1] 0.0001243198Chlorophyll
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).## Warning: Removed 21 rows containing non-finite values (stat_summary).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 198 65.844 0.3043 0.8223
## Residuals 1786 386473 216.390
- R.squared
## [1] 0.0005108494Flavonol
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).## Warning: Removed 21 rows containing non-finite values (stat_summary).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 0.012 0.004060 0.0728 0.9746
## Residuals 1786 99.618 0.055777
- R.squared
## [1] 0.0001222632Height 2018
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).## Warning: Removed 89 rows containing non-finite values (stat_summary).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 15817 5272.4 22.479 2.826e-14 ***
## Residuals 1718 402957 234.6
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.03776989Height 2019
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).## Warning: Removed 90 rows containing non-finite values (stat_summary).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 23664 7887.8 33.389 < 2.2e-16 ***
## Residuals 1717 405626 236.2
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.05512251Height Difference 2018-2019
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).## Warning: Removed 90 rows containing non-finite values (stat_summary).
- ANOVA
## Analysis of Variance Table
##
## Response: F1$HD5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 1938 646.10 2.9175 0.03306 *
## Residuals 1717 380245 221.46
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.005124903Flowering and Flowering Levels
Flowering refers to presence or not of flowers, Flower Level refers to a measure relating to the number of flowers present (0 = no flowers, 1 = 1-10, 2 = 10-20, 3 = 20+)
Anthocyanin
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).## Warning: Removed 21 rows containing non-finite values (stat_summary).
- ANOVA Flowering Level
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 0.0028 0.00093363 0.543 0.6529
## Residuals 1786 3.0709 0.00171943
- R.squared Flowering Level
## [1] 0.0009112453- T.tests comparing Flowering Levels and Anthocyanin
##
## Welch Two Sample t-test
##
## data: FLWR0$Anth and FLWR1$Anth
## t = 0.025664, df = 17.375, p-value = 0.9798
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.008423762 0.008631570
## sample estimates:
## mean of x mean of y
## -0.0001864908 -0.0002903948##
## Welch Two Sample t-test
##
## data: FLWR0$Anth and FLWR2$Anth
## t = 0.2922, df = 10.049, p-value = 0.7761
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.006353989 0.008273500
## sample estimates:
## mean of x mean of y
## -0.0001864908 -0.0011462463##
## Welch Two Sample t-test
##
## data: FLWR0$Anth and FLWR3$Anth
## t = -1.1298, df = 10.172, p-value = 0.2845
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.014848706 0.004841807
## sample estimates:
## mean of x mean of y
## -0.0001864908 0.0048169586##
## Welch Two Sample t-test
##
## data: FLWR1$Anth and FLWR2$Anth
## t = 0.1717, df = 22.843, p-value = 0.8652
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.009459314 0.011171017
## sample estimates:
## mean of x mean of y
## -0.0002903948 -0.0011462463##
## Welch Two Sample t-test
##
## data: FLWR1$Anth and FLWR3$Anth
## t = -0.88018, df = 21.286, p-value = 0.3886
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.017164673 0.006949967
## sample estimates:
## mean of x mean of y
## -0.0002903948 0.0048169586##
## Welch Two Sample t-test
##
## data: FLWR2$Anth and FLWR3$Anth
## t = -1.1256, df = 15.954, p-value = 0.277
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.017196954 0.005270544
## sample estimates:
## mean of x mean of y
## -0.001146246 0.004816959## Warning: Removed 21 rows containing non-finite values (stat_boxplot).## Warning: Removed 21 rows containing non-finite values (stat_summary).
- ANOVA Flowering Presence
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 0.00039 0.00039351 0.2289 0.6324
## Residuals 1788 3.07330 0.00171885
- R.squared Flowering Presence
## [1] 0.0001280242Chlorophyll
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).## Warning: Removed 21 rows containing non-finite values (stat_summary).
- ANOVA Flowering Level
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 1461 487.00 2.2579 0.07985 .
## Residuals 1786 385210 215.68
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flowering Level
## [1] 0.003778413- T.tests comparing Flowering Levels and Chlorophyll
##
## Welch Two Sample t-test
##
## data: FLWR0$Chl and FLWR1$Chl
## t = -1.3501, df = 18.737, p-value = 0.1931
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -3.4526591 0.7464858
## sample estimates:
## mean of x mean of y
## -0.2203429 1.1327437##
## Welch Two Sample t-test
##
## data: FLWR0$Chl and FLWR2$Chl
## t = -3.0493, df = 9.63, p-value = 0.01279
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -5.7911270 -0.8863768
## sample estimates:
## mean of x mean of y
## -0.2203429 3.1184090##
## Welch Two Sample t-test
##
## data: FLWR0$Chl and FLWR3$Chl
## t = 0.70751, df = 10.428, p-value = 0.4948
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.844508 3.574981
## sample estimates:
## mean of x mean of y
## -0.2203429 -1.0855790##
## Welch Two Sample t-test
##
## data: FLWR1$Chl and FLWR2$Chl
## t = -1.4075, df = 19.522, p-value = 0.175
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -4.9330444 0.9617139
## sample estimates:
## mean of x mean of y
## 1.132744 3.118409##
## Welch Two Sample t-test
##
## data: FLWR1$Chl and FLWR3$Chl
## t = 1.4669, df = 19.505, p-value = 0.1583
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.9413134 5.3779589
## sample estimates:
## mean of x mean of y
## 1.132744 -1.085579##
## Welch Two Sample t-test
##
## data: FLWR2$Chl and FLWR3$Chl
## t = 2.6688, df = 16.937, p-value = 0.01623
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.8795891 7.5283869
## sample estimates:
## mean of x mean of y
## 3.118409 -1.085579## Warning: Removed 21 rows containing non-finite values (stat_boxplot).## Warning: Removed 21 rows containing non-finite values (stat_summary).
- ANOVA Flowering Presence
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 19 18.847 0.0872 0.7679
## Residuals 1788 386652 216.248
- R.squared Flowering Presence
## [1] 4.87422e-05Flavonol
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).## Warning: Removed 21 rows containing non-finite values (stat_summary).
- ANOVA Flowering Levels
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 0.574 0.191220 3.4477 0.01606 *
## Residuals 1786 99.056 0.055463
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flowering Levels
## [1] 0.005757915- T.tests comparing Flowering Levels and Flavonol
##
## Welch Two Sample t-test
##
## data: FLWR0$Flav and FLWR1$Flav
## t = -0.19352, df = 20.332, p-value = 0.8485
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.04944842 0.04104444
## sample estimates:
## mean of x mean of y
## -0.0047609014 -0.0005589119##
## Welch Two Sample t-test
##
## data: FLWR0$Flav and FLWR2$Flav
## t = -2.2376, df = 8.9795, p-value = 0.05211
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.1555838602 0.0008748158
## sample estimates:
## mean of x mean of y
## -0.004760901 0.072593621##
## Welch Two Sample t-test
##
## data: FLWR0$Flav and FLWR3$Flav
## t = -0.58781, df = 9.9953, p-value = 0.5697
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.10202255 0.05943198
## sample estimates:
## mean of x mean of y
## -0.004760901 0.016534383##
## Welch Two Sample t-test
##
## data: FLWR1$Flav and FLWR2$Flav
## t = -1.8689, df = 13.816, p-value = 0.08299
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.15721039 0.01090532
## sample estimates:
## mean of x mean of y
## -0.0005589119 0.0725936208##
## Welch Two Sample t-test
##
## data: FLWR1$Flav and FLWR3$Flav
## t = -0.42086, df = 14.853, p-value = 0.6799
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.1037374 0.0695508
## sample estimates:
## mean of x mean of y
## -0.0005589119 0.0165343828##
## Welch Two Sample t-test
##
## data: FLWR2$Flav and FLWR3$Flav
## t = 1.1508, df = 16.999, p-value = 0.2658
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.04672184 0.15884031
## sample estimates:
## mean of x mean of y
## 0.07259362 0.01653438## Warning: Removed 21 rows containing non-finite values (stat_boxplot).## Warning: Removed 21 rows containing non-finite values (stat_summary).
- ANOVA Flowering Presence
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 0.24 0.240050 4.3184 0.03784 *
## Residuals 1788 99.39 0.055587
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flowering Presence
## [1] 0.002409418Height 2018
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).## Warning: Removed 89 rows containing non-finite values (stat_summary).
- ANOVA Flowering Levels
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 11639 3879.6 16.371 1.718e-10 ***
## Residuals 1718 407135 237.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flowering Levels
## [1] 0.02779275- T.tests comparing Flowering Levels and 2018 Height
##
## Welch Two Sample t-test
##
## data: FLWR0$H18 and FLWR1$H18
## t = -1.6305, df = 17.703, p-value = 0.1207
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -18.48037 2.34066
## sample estimates:
## mean of x mean of y
## -2.410131 5.659726##
## Welch Two Sample t-test
##
## data: FLWR0$H18 and FLWR2$H18
## t = -0.81929, df = 6.4906, p-value = 0.4417
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -22.95103 11.27931
## sample estimates:
## mean of x mean of y
## -2.410131 3.425728##
## Welch Two Sample t-test
##
## data: FLWR0$H18 and FLWR3$H18
## t = -1.5807, df = 9.3853, p-value = 0.147
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -19.310608 3.365938
## sample estimates:
## mean of x mean of y
## -2.410131 5.562204##
## Welch Two Sample t-test
##
## data: FLWR1$H18 and FLWR2$H18
## t = 0.26453, df = 11.816, p-value = 0.7959
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -16.19812 20.66612
## sample estimates:
## mean of x mean of y
## 5.659726 3.425728##
## Welch Two Sample t-test
##
## data: FLWR1$H18 and FLWR3$H18
## t = 0.014376, df = 20.604, p-value = 0.9887
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -14.02649 14.22153
## sample estimates:
## mean of x mean of y
## 5.659726 5.562204##
## Welch Two Sample t-test
##
## data: FLWR2$H18 and FLWR3$H18
## t = -0.25133, df = 11.217, p-value = 0.8061
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -20.80233 16.52937
## sample estimates:
## mean of x mean of y
## 3.425728 5.562204## Warning: Removed 89 rows containing non-finite values (stat_boxplot).## Warning: Removed 89 rows containing non-finite values (stat_summary).
- ANOVA Flower Presence
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 2126 2125.89 8.776 0.003094 **
## Residuals 1720 416648 242.24
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flower Presence
## [1] 0.005076449Height 2019
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).## Warning: Removed 90 rows containing non-finite values (stat_summary).
- ANOVA Flowering Level
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 8766 2922.09 11.931 9.858e-08 ***
## Residuals 1717 420523 244.92
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flowering Level
## [1] 0.02042042- T.tests comparing Flowering Levels and 2019 Height
##
## Welch Two Sample t-test
##
## data: FLWR0$H19 and FLWR1$H19
## t = -1.7634, df = 18.363, p-value = 0.09447
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -17.725963 1.535942
## sample estimates:
## mean of x mean of y
## -1.992529 6.102482##
## Welch Two Sample t-test
##
## data: FLWR0$H19 and FLWR2$H19
## t = -0.12465, df = 6.2813, p-value = 0.9047
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -24.14341 21.77867
## sample estimates:
## mean of x mean of y
## -1.9925285 -0.8101606##
## Welch Two Sample t-test
##
## data: FLWR0$H19 and FLWR3$H19
## t = 0.3993, df = 9.2524, p-value = 0.6987
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -9.983022 14.284387
## sample estimates:
## mean of x mean of y
## -1.992529 -4.143211##
## Welch Two Sample t-test
##
## data: FLWR1$H19 and FLWR2$H19
## t = 0.66835, df = 8.7152, p-value = 0.5212
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -16.60158 30.42687
## sample estimates:
## mean of x mean of y
## 6.1024818 -0.8101606##
## Welch Two Sample t-test
##
## data: FLWR1$H19 and FLWR3$H19
## t = 1.5106, df = 18.391, p-value = 0.1479
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -3.982633 24.474019
## sample estimates:
## mean of x mean of y
## 6.102482 -4.143211##
## Welch Two Sample t-test
##
## data: FLWR2$H19 and FLWR3$H19
## t = 0.31093, df = 9.5696, p-value = 0.7625
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -20.69819 27.36429
## sample estimates:
## mean of x mean of y
## -0.8101606 -4.1432112## Warning: Removed 89 rows containing non-finite values (stat_boxplot).## Warning: Removed 89 rows containing non-finite values (stat_summary).
- ANOVA Flower Presence
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 343 342.61 1.373 0.2415
## Residuals 1719 428947 249.53
- R.squared Flower Presence
## [1] 0.0007980757Height Difference 2018-2019
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).## Warning: Removed 90 rows containing non-finite values (stat_summary).
- ANOVA Flowering Level
## Analysis of Variance Table
##
## Response: F1$HD5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 11642 3880.7 17.982 1.719e-11 ***
## Residuals 1717 370541 215.8
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flowering Level
## [1] 0.0305669- T.tests comparing Flowering Levels and 2018-19 Height Differences
##
## Welch Two Sample t-test
##
## data: FLWR0$HD5 and FLWR1$HD5
## t = 0.0726, df = 22.1, p-value = 0.9428
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -6.781665 7.273837
## sample estimates:
## mean of x mean of y
## 0.6780263 0.4319402##
## Welch Two Sample t-test
##
## data: FLWR0$HD5 and FLWR2$HD5
## t = 1.4803, df = 9.0022, p-value = 0.1729
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -2.604488 12.467963
## sample estimates:
## mean of x mean of y
## 0.6780263 -4.2537116##
## Welch Two Sample t-test
##
## data: FLWR0$HD5 and FLWR3$HD5
## t = 2.0307, df = 9.4119, p-value = 0.07149
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.10757 21.88518
## sample estimates:
## mean of x mean of y
## 0.6780263 -9.7107801##
## Welch Two Sample t-test
##
## data: FLWR1$HD5 and FLWR2$HD5
## t = 1.0896, df = 17.451, p-value = 0.2907
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -4.369425 13.740729
## sample estimates:
## mean of x mean of y
## 0.4319402 -4.2537116##
## Welch Two Sample t-test
##
## data: FLWR1$HD5 and FLWR3$HD5
## t = 1.7507, df = 14.317, p-value = 0.1014
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -2.257682 22.543123
## sample estimates:
## mean of x mean of y
## 0.4319402 -9.7107801##
## Welch Two Sample t-test
##
## data: FLWR2$HD5 and FLWR3$HD5
## t = 0.94742, df = 12.738, p-value = 0.3611
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -7.012502 17.926639
## sample estimates:
## mean of x mean of y
## -4.253712 -9.710780## Warning: Removed 90 rows containing non-finite values (stat_boxplot).## Warning: Removed 90 rows containing non-finite values (stat_summary).
- ANOVA Flowering Presence
## Analysis of Variance Table
##
## Response: F1$HD5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 4205 4205.2 19.125 1.298e-05 ***
## Residuals 1719 377978 219.9
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared Flowering Presence
## [1] 0.01111171Measure Correlations
Plots
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 110 rows containing non-finite values (stat_smooth).## Warning: Removed 110 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 21 rows containing non-finite values (stat_smooth).## Warning: Removed 21 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 110 rows containing non-finite values (stat_smooth).## Warning: Removed 110 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 90 rows containing non-finite values (stat_smooth).## Warning: Removed 90 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 90 rows containing non-finite values (stat_smooth).
## Warning: Removed 90 rows containing missing values (geom_point).## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 90 rows containing non-finite values (stat_smooth).
## Warning: Removed 90 rows containing missing values (geom_point).
### Anthocyanin and Chlorophyll
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Chl5 1 0.33366 0.33366 217.73 < 2.2e-16 ***
## Residuals 1788 2.74003 0.00153
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.1085545Anthocyanin and Flavonol
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flav5 1 0.08082 0.080820 48.283 5.148e-12 ***
## Residuals 1788 2.99288 0.001674
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.02629407Anothcyanin and Height 2018
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H185 1 0.00199 0.0019900 1.1487 0.284
## Residuals 1699 2.94338 0.0017324
- R.squared
## [1] 0.0006756401Anthocyanin and Height 2019
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195 1 0.0000 0.00000073 4e-04 0.9836
## Residuals 1699 2.9454 0.00173359
- R.squared
## [1] 2.490926e-07Anthocyanin and Height Difference Between 2018 and 2019
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 0.00193 0.0019302 1.1283 0.2883
## Residuals 1699 2.90657 0.0017108
- R.squared
## [1] 0.0007111262Chlorophyll and Flavonol
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flav5 1 0.08082 0.080820 48.283 5.148e-12 ***
## Residuals 1788 2.99288 0.001674
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.02629407Chlorophyll and Height 2018
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H185 1 414 413.56 1.9052 0.1677
## Residuals 1699 368794 217.07
- R.squared
## [1] 0.001120119Chlorophyll and Height 2019
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195 1 78 78.221 0.36 0.5486
## Residuals 1699 369130 217.263
- R.squared
## [1] 0.0002118618Chlorophyll and Height Difference Between 2018 and 2019
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 197 196.57 0.901 0.3426
## Residuals 1699 370658 218.16
- R.squared
## [1] 0.0003842085Flavonol and Height 2018
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H185 1 0.073 0.073328 1.3145 0.2517
## Residuals 1699 94.773 0.055782
- R.squared
## [1] 0.0007731187Flavonol and Height 2019
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195 1 0.205 0.204977 3.6797 0.05525 .
## Residuals 1699 94.642 0.055704
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.002161139Flavonol and Height Difference Between 2018 and 2019
- ANOVA
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 0.584 0.58427 10.637 0.001131 **
## Residuals 1699 93.324 0.05493
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.006134827Height 2018 and 2019
- ANOVA
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195 1 125710 125710 740.77 < 2.2e-16 ***
## Residuals 1719 291720 170
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.3011528Height 2018 and Height Difference Between 2018 and 2019
- ANOVA
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 89593 89593 469.78 < 2.2e-16 ***
## Residuals 1719 327837 191
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.2148603Height 2019 and Height Difference Between 2018 and 2019
- ANOVA
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 101633 101633 533.2 < 2.2e-16 ***
## Residuals 1719 327656 191
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
- R.squared
## [1] 0.2148603